On the convergence of two sequential Monte Carlo methods for maximum a posteriori sequence estimation and stochastic global optimization.
Joaquín MíguezDan CrisanPetar M. DjuricPublished in: Stat. Comput. (2013)
Keyphrases
- global optimization
- maximum a posteriori
- map estimation
- markov random field
- gauss markov random fields
- maximum likelihood
- image reconstruction
- label field
- particle swarm optimization
- expectation maximization
- model parameters are estimated
- bayesian framework
- em algorithm
- posterior distribution
- sequential monte carlo methods
- inverse problems
- energy function
- image segmentation
- mrf model